Business users create and modify fraud rules without engineering help, so you adapt to new fraud patterns in hours, not sprints.
97% fewer false positives80% less fraud20% more approvals
Your Fraud Filters Are Blocking Good Customers
FraudNet combines custom machine learning, a no-code rules engine, and a global anti-fraud network to stop real fraud in real time - without punishing legitimate transactions.
Custom pricing based on your volume and requirements.
Trusted by teams at
CitibankMastercardRivertyBokuArvatoAcimaNelnetPlanetPayment
97%reduction in false positives
80%reduction in fraud
20%boost in approval rates
What it does
One platform, every layer of fraud defense
Detection, compliance, and case management working from the same data and the same models.
No-code rules engine
Business users create and modify fraud rules without engineering help, so you adapt to new fraud patterns in hours, not sprints.
Real-time risk scoring
Instant AI assessment of every transaction and user, with anomaly detection that flags suspicious behavior as it happens.
Custom AI models
Supervised Machine Learning, Graph Neural Networks, and Generative AI, trained on your data for sophisticated pattern recognition.
Global Anti-Fraud Network
Collective intelligence pooled across the FraudNet user base, so you see fraud patterns beyond your own transaction history.
Compliance suite
AML and KYC verification, entity screening, and transaction monitoring integrated directly into your fraud workflows.
Case management
End-to-end workflow management for fraud investigations, from alert to resolution, with full tracking along the way.
Flexible dashboards
Customizable analytics and reporting interfaces that surface real-time insights for fraud, risk, and compliance teams.
Learning Loop
Every outcome feeds back into the models, so detection accuracy keeps improving as fraud tactics shift.
The case for change
Legacy fraud tools cost you twice
They let new fraud schemes through while flagging honest customers, and your team pays for both mistakes.
The old way
- ×High false positive rates create customer friction and lost revenue
- ×Fraud tactics evolve faster than static rules can keep up
- ×Manual reviews and investigations drain time and resources
- ×Compliance obligations across jurisdictions pile onto already stretched teams
- ×Multiple point solutions for fraud, compliance, and risk never work together
The FraudNet way
- ✓AI-powered risk scoring evaluates every transaction and user instantly
- ✓Graph Neural Networks and Generative AI uncover patterns and entity relationships humans miss
- ✓A Learning Loop feeds outcomes back into models so accuracy improves continuously
- ✓AML, KYC, entity screening, and transaction monitoring built into one platform
- ✓One end-to-end system with data orchestration and enrichment included
Getting started
From raw data to real-time decisions
A simple route from setup to steady output.
Ingest and enrich
Real-time transaction and user data flows in through APIs and SDKs, then gets enriched with signals from the Global Anti-Fraud Network and third-party sources.
Analyze with AI
Graph Neural Networks and Generative AI models analyze patterns and relationships between entities across your entire dataset.
Decide in real time
The decision engine combines ML model outputs with your no-code rules to generate risk scores and return decisions via RESTful APIs and webhooks.
Learn and improve
The Learning Loop feeds outcomes back into the models, continuously refining accuracy while the orchestration layer keeps every step compliant.
Outcomes
What customers say
“FraudNet flexibility has helped our AfterPay business grow by allowing us to meet our increasingly complex customer and country requirements.”
“FraudNet's combination of customized machine learning and flexible rules management has been transformative.”
FAQ
Questions we hear most
What results can we expect?+
Companies implementing FraudNet typically see a 97% reduction in false positives, an 80% reduction in fraud, and a 20% boost in approval rates.
Do we need technical expertise to run it?+
No. The platform features a low-code/no-code rules engine and flexible dashboards, so business users can build and adjust fraud rules without engineering support.
What AI technologies does FraudNet use?+
FraudNet employs Supervised Machine Learning, Graph Neural Networks, and Generative AI for fraud detection and risk assessment, with a Learning Loop that continuously improves accuracy.
Which industries does FraudNet serve?+
FraudNet primarily serves Payments, Financial Services, Fintechs, and Commerce, with customized fraud prevention and risk management for each.
What compliance capabilities are included?+
AML and KYC verification, entity screening and monitoring, and transaction monitoring are all built into the platform.
How does pricing work?+
Pricing is customized to your requirements and scale of operations. Book a call with our team and we will scope it with you.
Get started
See what FraudNet catches that your current stack misses
Book a call and we will walk through your fraud, compliance, and approval-rate goals with you.
Book a call with our team→